Facebook pixel tracking

The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

Contact Info
Website thesai.org
Follow Us
Contact Info
Follow Us
Research Article | Open Access |

Predicting Aircraft Engine Failures using Artificial Intelligence

Author 1: Asmae BENTALEB Author 2: Kaoutar TOUMLAL Author 3: Jaafar ABOUCHABAKA
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 15, No. 2 · Published 2024

DOI: https://doi.org/10.14569/IJACSA.2024.0150295

Abstract

Nowadays, the aviation sector continues to develop especially with the emergence of new technologies, and solutions. Hence, there is an increasing demand for enhanced safety and operational efficiency in the aviation industry. As to guarantee this safety, the aircraft’s engines must be monitored, controlled and maintained, however in an efficient way. Thus, the research community is working continuously in order to provide solutions that are efficient and cost effective. Artificial intelligence and more specifically machine learning models have been employed in this sense. Here comes the proposition of this article. It presents solutions implementing predictive maintenance using machine learning models. They help in predicting aircraft’s failures. This is in order to avoid operations of unscheduled maintenance and disruptions of services.

Keywords

How to Cite this Article

BENTALEB, A., TOUMLAL, K., & ABOUCHABAKA, J. (2024). Predicting Aircraft Engine Failures using Artificial Intelligence. International Journal of Advanced Computer Science and Applications, 15(2). https://doi.org/10.14569/IJACSA.2024.0150295

BENTALEB, Asmae, et al.. "Predicting Aircraft Engine Failures using Artificial Intelligence." International Journal of Advanced Computer Science and Applications, vol. 15, no. 2, 2024, https://doi.org/10.14569/IJACSA.2024.0150295.

@article{BENTALEB2024,
  title     = {Predicting Aircraft Engine Failures using Artificial Intelligence},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {2},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Asmae BENTALEB and Kaoutar TOUMLAL and Jaafar ABOUCHABAKA},
  doi       = {10.14569/IJACSA.2024.0150295},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150295}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.